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Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in…

Neural and Evolutionary Computing · Computer Science 2016-12-20 Alyssa M Adams , Hector Zenil , Paul CW Davies , Sara I Walker

Discrete dynamical models underpin systems biology, but we still lack substrate-agnostic diagnostics for identifying finite-horizon dynamical signatures that may be relevant to open-ended evolution (OEE), such as the recurrent production of…

Populations and Evolution · Quantitative Biology 2026-05-27 Amahury J. López-Díaz , Pedro Juan Rivera Torres , Gerardo L. Febres , Carlos Gershenson

A paper in the recent Artificial Life journal special issue on open-ended evolution (OEE) presents a simple evolving computational system that, it is claimed, satisfies all proposed requirements for OEE (Hintze, 2019). Analysis and…

Neural and Evolutionary Computing · Computer Science 2020-06-08 Tim Taylor

Open-ended evolutionary dynamics remains an elusive goal for artificial evolutionary systems. Many ideas exist in the biological literature beyond the basic Darwinian requirements of variation, differential reproduction and inheritance. I…

Neural and Evolutionary Computing · Computer Science 2015-07-28 Tim Taylor

Evolution by natural selection can be seen an algorithm for generating creative solutions to difficult problems. More precisely, evolution by natural selection is a class of algorithms that share a set of properties. The question we address…

Neural and Evolutionary Computing · Computer Science 2018-06-22 Peter D. Turney

This paper presents a theory of systemic undecidability, reframing incomputability as a structural property of systems rather than a localized feature of specific functions or problems. We define a notion of causal embedding and prove a…

Logic in Computer Science · Computer Science 2025-09-03 Seth Bulin

This article presents a formal model demonstrating that genuine autonomy, the ability of a system to self-regulate and pursue objectives, fundamentally implies computational unpredictability from an external perspective. we establish…

Artificial Intelligence · Computer Science 2025-09-17 Poria Azadi

Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species.…

Adaptation and Self-Organizing Systems · Physics 2011-12-15 James M Whitacre , Axel Bender

Engineering long-running computing systems that achieve their goals under ever-changing conditions pose significant challenges. Self-adaptation has shown to be a viable approach to dealing with changing conditions. Yet, the capabilities of…

Software Engineering · Computer Science 2023-03-28 Danny Weyns , Jesper Andersson

Computing systems are omnipresent; their sustainability has become crucial for our society. A key aspect of this sustainability is the ability of computing systems to cope with the continuous change they face, ranging from dynamic operating…

Software Engineering · Computer Science 2022-04-15 Danny Weyns , Thomas Baeck , Rene Vidal , Xin Yao , Ahmed Nabil Belbachir

Given the complexity of modern software systems, it is of great importance that such systems be able to autonomously modify themselves, i.e., self-adapt, with minimal human supervision. It is critical that this adaptation both results in…

Software Engineering · Computer Science 2022-05-13 Todd Wareham , Ronald de Haan

Evolvability is the capacity to evolve. This paper introduces a simple computational model of evolvability and demonstrates that, under certain conditions, evolvability can increase indefinitely, even when there is no direct selection for…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Peter D. Turney

Observations are an essential component of the simulation based studies on artificial-evolutionary systems (AES) by which entities are identified and their behavior is observed to uncover higher-level "emergent" phenomena. Because of the…

Neural and Evolutionary Computing · Computer Science 2018-08-13 Janardan Misra

The idea that there are any large-scale trends in the evolution of biological organisms is highly controversial. It is commonly believed, for example, that there is a large-scale trend in evolution towards increasing complexity, but…

Neural and Evolutionary Computing · Computer Science 2021-06-08 Peter D. Turney

This paper presents a high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems. Drawing upon earlier work by Banzhaf et al., three different kinds of open-endedness are…

Neural and Evolutionary Computing · Computer Science 2019-02-22 Tim Taylor

Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simplified problems and optimization algorithms that sometimes miss expectations in real-world…

There are several forms of irreducibility in computing systems, ranging from undecidability to intractability to nonlinearity. This paper is an exploration of the conceptual issues that have arisen in the course of investigating speed-up…

Computational Complexity · Computer Science 2011-06-24 Hector Zenil , Fernando Soler-Toscano , Joost J. Joosten

Complex change is often described as "evolutionary" in economics, policy, and technology, yet most system dynamics models remain constrained to fixed state spaces and equilibrium-seeking behavior. This paper argues that evolutionary…

Populations and Evolution · Quantitative Biology 2026-02-19 Dan Adler

Vision systems in nature show remarkable diversity, from simple light-sensitive patches to complex camera eyes with lenses. While natural selection has produced these eyes through countless mutations over millions of years, they represent…

Artificial Intelligence · Computer Science 2025-02-14 Kushagra Tiwary , Aaron Young , Zaid Tasneem , Tzofi Klinghoffer , Akshat Dave , Tomaso Poggio , Dan-Eric Nilsson , Brian Cheung , Ramesh Raskar

Information theoretic analysis of large evolved programs produced by running genetic programming for up to a million generations has shown even functions as smooth and well behaved as floating point addition and multiplication loose entropy…

Neural and Evolutionary Computing · Computer Science 2021-12-03 W. B. Langdon
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